Dana-Farber Cancer Institute (DFCI): Identification of Therapeutic Targets: Adult and Pediatric Cancer Types

The Dana Farber Cancer Institute CTD2 Center focuses on the use of high-throughput genetic and bioinformatic approaches to identify and credential oncogenes and co-dependencies in cancers. This Center aims to provide the cancer research community with information that will facilitate the prioritization of targets based on both genomic and functional evidence, inform the most appropriate genetic context for downstream mechanistic and validation studies, and enable the translation of this information into therapeutics and diagnostics.

The Dana-Farber CTD2 center’s Project Achilles is a systematic effort that aims to identify cancer genetic dependencies and link them to molecular characteristics in order to prioritize targets for therapeutic development and identify the patient population that might benefit from such targets. The ongoing project aims at screening hundreds of cell lines of a variety of lineages, including cell lines derived from both solid and hematopoietic tumors. An expanding suite of computational and analytical tools is being developed to derive biomarker-dependency relationships.

Read the abstracts: Cowley et al., 2014Cheung et al., 2011, and Aguirre et al., 2016

Experimental Approaches

The Dana Farber Cancer Institute CTD2 Center uses pooled genome-wide genetic perturbation reagents (shRNAs or Cas9/sgRNAs) to silence or knock-out individual genes and identify genes that affect cell survival. Massively parallel pooled shRNA or sgRNA screens were performed in cancer cell lines to identify genes that are required for cell proliferation and/or viability.

In the case of shRNAs, a genome-scale, lentivirally delivered shRNA library is used, interrogating ~11,000 genes by on average 5 shRNAs per gene. The proliferation effect of each shRNA in each cell line was assessed by transducing a population of 11M cells with one shRNA-virus per cell and determining the relative enrichment or depletion of each of the 54,020 shRNAs after 16 population doublings. The abundance of shRNA constructs relative to the initial DNA plasmid pool was measured by either Affymetrix custom barcode microarrays (102 cell lines, Cheung et al.) or using Next Generation Sequencing (216 cell lines, Cowley et al.). Similarly, for Cas9/sgRNA screening, a genome-scale lentivirally delivered sgRNA library is transduced into cancer cell lines expressing the Cas9 nuclease.  Cell line dependencies on ~19,000 genes were assessed by on average 6 sgRNAs per gene in this library (GeCKOv2).  The relative enrichment or depletion of each of the 123,411 sgRNAs after 21-28 days in culture was assessed to determine the proliferation effect of each. The abundance of sgRNA constructs relative to the initial DNA plasmid pool was measured by using Next Generation Sequencing (33 cell lines, Aguirre et al.). All the cell lines were screened using standardized conditions to best assess differential genetic dependencies across cell lines.

Read the detailed Experimental Approaches: Cowley et al., 2014Cheung et al., 2011, and Aguirre et al., 2016


Access the Raw/Analyzed Data (DCC)

Access the Dashboard Submission(s)


For questions, please contact Joshua Dempster.


  1. Shao D, et al. (2013) ATARis: Computational quantification of gene suppression phenotypes from multisample RNAi screens. Genome Res. 23(4):665-678 (PMID: 23269662)
Last updated: September 14, 2018